Introduction & Motivation:

According to the United States Census Bureau, households with same-sex couples have a higher median income than households with opposite-sex couples: $107,200 and $96,930 respectivly. This statistic however does not take into account many variables. For example, when the data is diaggregated by gender, the median household income of same-sex female households is only $95,720 which is less than the median for opposite-sex couples. Our project disaggregates the household incomes of same-sex and opposite-sex couples by race (white and not-white.) Since same-sex married couples account for only 1% of the married couple households in the United States and only 5.1% of unmarried couples, we will determine the median as a percentage of the total population of their grouping. We also do not plan on taking into account married or unmarried status since opposite-sex couples have a much higher marriage rate (88%) than same-sex couples (58%). Disaggregating the data will reveal whether or not same-sex couples of different races actually have a higher median income as opposite-sex couples of different races.

One challenge will be accounting for the races of both people in the relationship. We could either use only the race of the first person in the couple to determine the couple’s race (knowing this oversimplification would cause a certain amount of error), or we could try to find the race of both people in the couple and duplicate the data point for each racial category that it fits under. Alternately, we could exclude interracial couples from the data set, but that means that we would be cutting down the population of same-sex couples even more because a large percentage are interracial.




Roadmap

In the following sections of data visualization and analysis, we split the analysis into three parts, each one focusing on disaggregating a different aspect of personal identity. Part 1 disaggregates by couple type by doing an equity analysis of personal income by race for first same-sex and then opposite sex couples. This the broadest analysis, and displays data for three geographic regions: the whole USA, Florida, and California. Parts 2 and 3 do a deeper dive into California data alone. Part 1 disaggregates the data by race, performing equity analyses of personal income by couple-type for each race individually. Part 3 examines the impact of gender on equity, (Note: gender and sex are used interchangeably in this report–the only options for sex given on the survey are male and female, with no question about gender identity).




Shiny Dashboard

Part 1: Couple Type

Equity Analysis of Personal Income by Race, Disaggregated by Couple Type


USA:

Proportion of couples who are same-sex

To maintain a more observable color gradient, a few outliers were filtered out. Palm Springs was the largest and had 17.62% same-sex couples.

Most of the PUMA’s had between 0% and 2% same-sex couples. It is important to note that in this assignment the populations that we are comparing (Same-sex couples vs. Opposite Sex Couples) are vastly different sizes.

Some races were filtered out of the US and Florida maps so that they will be easier to compare to the California map. We filtered out these races because the same-sex sample size was too small.

Key Assumptions: We are assuming that the first two SPORDER (person numbers: 1, 2) are the two people in the relationship. Additionally, there are no census questions directly asking for sexualitys, but there are questions pertaining to the gender of the two heads of households and their marital status (married or unmarried). Since we are only working with couples data, the number of people that we are using in each data set is reduced. We are including unmarried couples and assuming that they are in a cohabitation agreement.


USA:

Same-sex equity analysis

Across the US, there are observable inequities among races within same-sex communities. White people make up a slightly disproportionate number of people making over $250,001 and also a disproportinatly low number of people making less than $20,000. Asian American people make up a consistent proportion of people at every level. Two or more Races makes up a disproportionate amount of people making less than $20,000. Black or African American people also make up a disproportinate number of people making less than $20,000 and then make up a disproportionately low number at higher income tiers ($50,000 and up.) This plot does suggest inequities that are particularly advantageous for white people and disadvantageous for black or African American people.


USA:

Opposite-sex equity analysis

Among people in opposite-sex relationships, similar trends prevail in the data however to a smaller degree. The proportions for White only and Two or More Races at every income tier are more consistent. Black or African American people make up a larger proportion of low-income people and a smaller proportion of high income people. Asian Americans on average make up a slightly larger proportion of high income people.


Florida:

Proportion of couples who are same-sex

To maintain a more observable color gradient, a few outliers were filtered out. The largest PUMA was in Fort Lauderdale and it had 6.88% same-sex couples.

We wanted to see how the inequities in another populous state would compare to the inequities in California. We chose Florida because it is the third largest state by population (after California and Texas), but it is also more diverse than Texas.


Florida:

Same-sex equity analysis

We included ‘Other Race’ in this plot because the results were interesting. Generally Florida’s personal income equity analysis among people in same-sex relationships is less equitable than the national equity analysis conducted above. White people make up a disproportionately high proportion of people making between $80,001 and $250,000 and they are the only race included that appears in the $200,000 to $250,000 tier. This is most likely due the a lower sample size. Asian people make up a very low proportion of the overall population however they make up a significantly larger proportion of people making $250,001 and more. Black or African American data is similar to the national data. They make up a disproportionately low proportion of the highest income tier and a disproportionately high proportion of the lowest income tier.


Florida:

Opposite-sex equity analysis

The results for the race-income equity analysis of people in opposite-sex relationships resembles the national results more than the equtiy analysis of people in same-sex relationships–Probably because the sample size is larger. Some other race alone and Black or African American alone make are disproportinaly represented in high income tiers ($80,000 and up.)


California:

Proportion of couples who are same-sex

For this map we decided to include the actual counts of people in same-sex relationships rather than the percentages.This is another reminder of the sample size and how low it is in reality.

To maintain a more observable color gradient, a few outliers were filtered out. Palm Springs was the largest and had 320 people same-sex relationships.


California:

Same-sex equity analysis

This equity analysis has the least consistent data of the three for same-sex (USA, Florida, California.) White Only make up a disproportiate ammount of people making $250,000 alone but other than that they are pretty proportionate at every tier. Asian alone make up a slightly higher proportion of people making $200,001 to $250,000 and a lower proportion of people making $250,000 or more. American Indians make up a slightly higher proportion of people making between $20,001 and $50,000. Two or more races is pretty proportionate at every income tier except ‘$250,000 or more.’ The most observable trend in Black or African American, which shrink in proportions as the income tier increases, but to a smaller degree than the other equity analysis’. The income tiers between $0 and $50,000 are consistent with the total population data.


California:

Opposite-sex equity analysis

This is the most consistent equity analysis. There is a much larger proportion of Asian people in California than in Florida or USA. This data suggests that there is more racial inequity within same-sex couple groupings than opposite-sex couple groupings.




Part 2: Race

Equity Analysis of Personal Income by Couple Type, Disaggregated by Race


All Races

See below for each race individually.

This map reveals the percentage of people within each PUMA that make below $50,000 dollars. Grey PUMAs are PUMAs that did not have same-sex couple data. The is a large range of data. Some PUMAs have 100% low income same-sex couples and there is also a PUMA that has 0%.

This map reveals the percentage of people within each PUMA that make below $50,000 dollars. Grey PUMAs are PUMAs that did not have opposite-sex couple data. This data is consistently arount the %40-%60 range.

There does not appear to be a large change in proportions across different income tiers. Same-sex couples make up a slightly high proportion of people making $200,001 to $250,000.


White Alone

This map reveals the percentage of people within each PUMA that make below $50,000 dollars. Grey PUMAs are PUMAs that did not have same-sex couple data.

This map reveals the percentage of people within each PUMA that make below $50,000. Grey PUMAs are PUMAs that did not have same-sex couple data.

There appears to be a low average percentage of people making less than $50,000. PUMAS that are located in the Bay Area and near cities like Los Angeles have lower percentage than more inland PUMAS.

There does not appear to be a large change in proportions across different income tiers


Black or African American alone

This map reveals the percentage of people within each PUMA that make below $50,000. Grey PUMAs are PUMAs that did not have same-sex couple data. There are many grey areas due to a small sample size and most of the PUMA’s appear to be low-income.

This map reveals the percentage of people within each PUMA that make below $50,000. Grey PUMAs are PUMAs that did not have same-sex couple data.

There does not appear to be a large change in proportions across different income tiers. Same-sex couples make up a larger proportion of people making $200,001 to $250,000.


Asian American Alone


American Indian alone


Two or More Races




Part 3: Sex

Equity Analysis of Personal Income by Race, Disaggregated by Sex

Equity Analysis of single gender and relationship type




Conclusion:

After performing these analysis, we are able to draw several conclusions….